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Ensemble decision trees

be applied to solve credit decisions problems. The method uses switching class labels techniques to construct complex classification system;

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Comparative Analysis of Deterministic and Nondeterministic Decision Trees

of deterministic, nondeterministic, and strongly nondeterministic decision trees for problem solving. Deterministic decision trees are widely used as;

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Comparative Analysis of Deterministic and Nondeterministic Decision Trees

of deterministic, nondeterministic, and strongly nondeterministic decision trees for problem solving. Deterministic decision trees are widely used as;

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Decision Tree and Ensemble Learning Based on Ant Colony Optimization

into one. This was decisive for choosing the material to be included in the book and determining its order of presentation. Decision trees are;

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Ensemble Classification Methods with Applications in R

An essential guide to two burgeoning topics in machine learning - classification trees and ensemble ;...

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Data Mining with Decision Trees

Decision trees have become one of the most powerful and popular approaches in knowledge discovery and data mining; it is the science;

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Decision Trees for Business Intelligence and Data Mining

This example-driven guide illustrates the application and operation of decision trees in data mining, business intelligence, business;

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Data Mining With Decision Trees

This is the first comprehensive book dedicated entirely to the field of decision trees in data mining and covers all aspects of this;

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Decision and Inhibitory Trees and Rules for Decision Tables with Many-valued Decisions

of data mining, knowledge discovery, and machine learning, especially those whose work involves decision tables with many-valued decisions. The;

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Decision and Inhibitory Trees and Rules for Decision Tables with Many-valued Decisions

of data mining, knowledge discovery, and machine learning, especially those whose work involves decision tables with many-valued decisions. The;

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Fault Trees

presented, as well as more recent algorithms based on binary decision diagrams (BDD).;

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DATA MINING and MACHINE LEARNING. CLASSIFICATION PREDICTIVE TECHNIQUES: SUPPORT VECTOR MACHINE, LOGISTIC REGRESSION, DISCRIMINANT ANALYSIS and DECISION TREES

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Proactive Data Mining with Decision Trees

introduces a novel splitting criterion for decision trees, termed maximal-utility, which maximizes the potential for enhancing profitability in the;

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Decision-Making Management

Decision-Making Management: A Tutorial and Applications provides practical guidance for researchers seeking to optimizing business;

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Applied Supervised Learning with Python

you've grasped the basics, you'll learn how to build and train your own models using advanced techniques such as decision trees, ensemble;

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Seeing the Forest for the Trees: A Manager's Guide to Applying Systems Thinking

Sherwood presents a managers guide to applying systems thinking and making ita part of daily decision making.;

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Handbook of Clinical Pediatric Endocrinology

(in treatment, diagnosis, etc.) boxes, a key weblinks box, a table comparing different society guidelines, diagnostic decision trees, therapeutics;

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Farms Trees and Farmers

in farmer tree-growing and the factors which influence decision-making. Eight case studies cover, among other topics, the need for tree products;

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Pro HTML5 Games

and parallax scrolling, and creating challenging levels with decision trees.;

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Decision Making in Medicine

This popular reference facilitates diagnostic and therapeutic decision making for a wide range of common and often complex problems faced;

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Combining Pattern Classifiers

: * Coverage of Bayes decision theory and experimental comparison of classifiers * Essential ensemble methods such as Bagging, Random forest, AdaBoost;

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Decision Making with Insight (with Insight.xla 2.0 and CD-ROM)

introduction to methods of decision making. This book and accompanying suite of Excel add-ins for quantitative analysis covers Monte Carlo simulation;

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What Every Engineer Should Know About Decision Making Under Uncertainty

Covering the prediction of outcomes for engineering decisions through regression analysis, this succinct and practical reference presents;

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Spatial Big Data Science

observation imagery big data. Specifically, the authors introduce several recent spatial classification techniques, such as spatial decision trees and;

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Stream Data Mining: Algorithms and Their Probabilistic Properties

heuristics, it highlights methods and algorithms that are mathematically justified. First, it describes how to adapt static decision trees to;

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Advances in Fuzzy Decision Making

in decision-making problems. It describes how to combine decision trees, clustering, multi-attribute decision-making algorithms and Monte Carlo;

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Statistical Methods in the Atmospheric Sciences

Statistical Methods in the Atmospheric Sciences, Fourth Edition, continues the tradition of tryi;...

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